The most often cited representative examples of conventional noise suppression methods are the spectrum subtraction method and the Wiener filter method. Other than these methods, various noise suppression methods are being researched and developed such as comb filters and adaptive filters.
FIG. 1 is a diagram which shows the structure of a noise suppresser using a conventional spectral subtraction method. FIG. 2 is a diagram which shows the structure of a noise suppresser that uses a conventional Wiener filter. As shown in FIG. 1 and FIG. 2, in the spectrum subtraction method or the Wiener filter method, a noise spectrum is generally estimated (measured) by a noise region, i.e. a time region in which audio is not included, and as a basic guideline, noise suppression is performed by subtracting the noise elements from the input signal. In any of these noise suppression methods, generally the noise spectrum is estimated according to the following equation and multiplied by the suppression coefficient α, which is a scaling factor for adjusting the noise suppression weight.|Y(f)|=|X(f)|−α|N(f)|
Note that X(f) expresses the input signal spectrum, N(f) the noise spectrum and Y(f) the signal spectrum after noise suppression is performed; | | stand for the absolute value of the signal. f expresses the frequency variable.
On the one hand, when the estimation accuracy of the noise spectrum decreases, musical noise particular to the spectrum subtraction method used is generated, due to causes such as excessive subtraction. Although the S/N ratio improves, there is the drawback that, after the noise is suppressed, musical noise such as a wispy digital sound remains.
One source of estimation accuracy deterioration in the noise spectrum is generated when environmental noise is not uniform. Since the noise spectrum is generally not uniform, the suppression coefficient α can be variable according to the environment, and it can be expected that a high noise suppression effect can be obtained. For example, noise suppressers have been proposed which calculate a noise suppression weight based not only on the present input signal spectrum and the average spectrum of the noise, but also on the standard deviation of the noise, and which are handled more suitably to the actual environmental noise (see for example, Patent Document 1). However, even the method in Patent Document 1 cannot process transient noise that does not correlate to the previous noise spectrum. Also, among AM (Amplitude Modulation), FM (Frequency Modulation) and other receivers, receivers are proposed which can obtain an extremely high noise suppression effect with noise estimation, by reading out and performing one-dimensional linear interpolation on the noise patterns that have been calculated and recorded beforehand (see for example, Patent Reference 2). This is because when changes in the noise relative to changes in the field strength are noted as causes of noise generation, the noise can be patterned according to the field strength since the circuits which cause noise generation differ according to the field strength.    Patent Reference 1: Japanese Laid-Open Patent No. 2003-316381 Publication    Patent Reference 2: Japanese Laid-Open Patent No. 2760240 Publication